What Do Older Canadians Think They Need to Walk Well?
Bibliographic record
Abstract
Purpose: To identify older Canadians’ perception of the importance of expert-generated elements of walking quality, and the contributors to and consequences of perceived walking quality. Method: Cross-sectional survey of 649 adults was conducted through a commercial participant panel, Hosted in Canada Surveys. Results: Of the 649 respondents, 75% were between 65 and 74 years old (25% ≥ 75) and 49% were women. The most important elements were foot, ankle, hip, and knee mobility with little difference in ranks across walking perception (Fr χ12 = 5.0, p > 0.05). People who were older by a decade were more likely to report poorer walking (POR: 1.4; 95% CI: 1.0, 1.7), as were women compared to men, and people who used a walking aid compared to none. Lung disease showed the highest association with a perception of not walking well (POR: 7.2; 95% CI: 3.7, 14.2). The odds of being willing to pay more for a technology to improve walking were always greater for those with a lower perception of their walking quality. Conclusions: People who perceived their walking quality as poor were more likely to report poorer health and were willing to pay more for a technology to improve walking. This supports the opportunity of leveraging wearable technologies to improve walking.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".